Measuring the Private and Social Returns to R&D: Unintended Spillovers versus Technology Markets

Pere Arqué-Castells, Daniel F. Spulber

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The canonical approach to measuring private and social returns to R&D assumes diffusion through spillovers. We develop a general framework that allows R&D to diffuse through both spillovers and voluntary technology transfers. To operationalize the framework, we create a data set of interactions in the market for technology between publicly held US firms. We use changes in tax incentives for R&D to identify causal effects. Taking market channels into account decreases the observed difference between social and private returns to R&D as compared with the canonical approach. The analysis suggests significant gains from trade in markets for technology.

Original languageEnglish (US)
Pages (from-to)1860-1918
Number of pages59
JournalJournal of Political Economy
Volume130
Issue number7
DOIs
StatePublished - Jul 2022

Funding

Assignment Dataset with us. We also thank participants in the 2018 Intellectual Property Statistics for Decision Makers (IPSDM) Conference, the 2018 Barcelona Graduate School of Economics (BGSE) Workshop on the Economics of Science and Innovation, the 2019 International Journal of Industrial Organization (IJIO) Conference, the 2019 Knowledge, Innovation, and Internationalization Strategies (KIIS) Workshop at the University of Valencia, the 2019 Workshop on Innovation and Firm Performance at the Universitat Rovira i Virgili, and internal seminars at the Collegio Carlo Alberto, the Eindhoven University of Technology, the Max Planck Institute for Innovation and Competition, Maastricht University, the University of Barcelona, the University of Groningen, the University of Mallorca, and the United Nations University–Maastricht Economic and Social Research Institute on Innovation and Technology (UNU-MERIT). Pere Arqué-Castells gratefully acknowledges support from Qualcomm. Daniel F. Spulber gratefully acknowledges research support from Qualcomm and the Kellogg School of Management. The views expressed are those of the authors and do not necessarily represent those of any of these institutions. Data are provided as supplementary material online. This paper was edited by Chad Syverson.

ASJC Scopus subject areas

  • Economics and Econometrics

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